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Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis.

Publication ,  Journal Article
Du, P; Zhang, X; Huang, C-C; Jafari, N; Kibbe, WA; Hou, L; Lin, SM
Published in: BMC Bioinformatics
November 30, 2010

BACKGROUND: High-throughput profiling of DNA methylation status of CpG islands is crucial to understand the epigenetic regulation of genes. The microarray-based Infinium methylation assay by Illumina is one platform for low-cost high-throughput methylation profiling. Both Beta-value and M-value statistics have been used as metrics to measure methylation levels. However, there are no detailed studies of their relations and their strengths and limitations. RESULTS: We demonstrate that the relationship between the Beta-value and M-value methods is a Logit transformation, and show that the Beta-value method has severe heteroscedasticity for highly methylated or unmethylated CpG sites. In order to evaluate the performance of the Beta-value and M-value methods for identifying differentially methylated CpG sites, we designed a methylation titration experiment. The evaluation results show that the M-value method provides much better performance in terms of Detection Rate (DR) and True Positive Rate (TPR) for both highly methylated and unmethylated CpG sites. Imposing a minimum threshold of difference can improve the performance of the M-value method but not the Beta-value method. We also provide guidance for how to select the threshold of methylation differences. CONCLUSIONS: The Beta-value has a more intuitive biological interpretation, but the M-value is more statistically valid for the differential analysis of methylation levels. Therefore, we recommend using the M-value method for conducting differential methylation analysis and including the Beta-value statistics when reporting the results to investigators.

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Published In

BMC Bioinformatics

DOI

EISSN

1471-2105

Publication Date

November 30, 2010

Volume

11

Start / End Page

587

Location

England

Related Subject Headings

  • Microarray Analysis
  • Data Interpretation, Statistical
  • DNA Methylation
  • CpG Islands
  • Bioinformatics
  • 49 Mathematical sciences
  • 46 Information and computing sciences
  • 31 Biological sciences
  • 08 Information and Computing Sciences
  • 06 Biological Sciences
 

Citation

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MLA
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Du, P., Zhang, X., Huang, C.-C., Jafari, N., Kibbe, W. A., Hou, L., & Lin, S. M. (2010). Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis. BMC Bioinformatics, 11, 587. https://doi.org/10.1186/1471-2105-11-587
Du, Pan, Xiao Zhang, Chiang-Ching Huang, Nadereh Jafari, Warren A. Kibbe, Lifang Hou, and Simon M. Lin. “Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis.BMC Bioinformatics 11 (November 30, 2010): 587. https://doi.org/10.1186/1471-2105-11-587.
Du P, Zhang X, Huang C-C, Jafari N, Kibbe WA, Hou L, et al. Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis. BMC Bioinformatics. 2010 Nov 30;11:587.
Du, Pan, et al. “Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis.BMC Bioinformatics, vol. 11, Nov. 2010, p. 587. Pubmed, doi:10.1186/1471-2105-11-587.
Du P, Zhang X, Huang C-C, Jafari N, Kibbe WA, Hou L, Lin SM. Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis. BMC Bioinformatics. 2010 Nov 30;11:587.
Journal cover image

Published In

BMC Bioinformatics

DOI

EISSN

1471-2105

Publication Date

November 30, 2010

Volume

11

Start / End Page

587

Location

England

Related Subject Headings

  • Microarray Analysis
  • Data Interpretation, Statistical
  • DNA Methylation
  • CpG Islands
  • Bioinformatics
  • 49 Mathematical sciences
  • 46 Information and computing sciences
  • 31 Biological sciences
  • 08 Information and Computing Sciences
  • 06 Biological Sciences